This paper describes a prototype telemedicine system for remote 3d radiation treatment planning. due to voluminous medical image data and image streams generated in interactive frame rate involved in the application, ...
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This paper describes a prototype telemedicine system for remote 3d radiation treatment planning. due to voluminous medical image data and image streams generated in interactive frame rate involved in the application, the importance of deploying adjustable lossy to lossless compression techniques is emphasized in order to achieve acceptable performance via various kinds of communication networks. In particular, the compression of the data substantially reduces the transmission time and therefore allows large-scale radiation distribution simulation and interactive volume visualization using remote supercomputing resources in a timely fashion. The compression algorithms currently used in the software we developed are JPEG and H.263 lossy methods and Lempel-Ziv (LZ77) lossless methods. Both objective and subjective assessment of the effect of lossy compression methods on the volume data are conducted. Favorable results are obtained showing that substantial compression ratio is achievable within distortion tolerance. From our experience, we conclude that 30dB (PSNR) is about the lower bound to achieve acceptable quality when applying lossy compression to anatomy volume data (e.g. CT). For computer simulateddata, much higher PSNR (up to 100dB) is expectable. This work not only introduces such novel approach for delivering medical services that will have significant impact on the existing cooperative image-based services, but also provides a platform for the physicians to assess the effects of lossy compression techniques on the diagnostic and aesthetic appearance of medical imaging.
We present a multilevel object modeling scheme adapted to storage and progressive transmission of complex 3d objects. Geometry and texture are encoded in terms of surface particles associated to a hierarchical space p...
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We present a multilevel object modeling scheme adapted to storage and progressive transmission of complex 3d objects. Geometry and texture are encoded in terms of surface particles associated to a hierarchical space partitioning via an octree. Proper ordering of surface particles results in a compact multilevel representation without increasing the size of the uni-resolution model which provides the highest level of detail. This compact representation can be progressively decoded by the viewer and transformed by a fast direct triangulation technique into a sequence of triangle meshes of increasing levels of detail. The proposed scheme is demonstrated with 3d models of real objects constructed by a shape from silhouette technique.
A new satellite instrument, GOMOS, will be launched on ESA39;s ENVISAT in year 2000 and will measure ozone with unprecedented long term accuracy and vertical resolution. GOMOS observes stellar occultations, anddete...
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A new satellite instrument, GOMOS, will be launched on ESA's ENVISAT in year 2000 and will measure ozone with unprecedented long term accuracy and vertical resolution. GOMOS observes stellar occultations, anddetermines ozone, NO2, NO3, aerosol, O2, H2O and possibly OClO concentrations from the ratio of two stellar spectra, one outside the atmosphere, one through the atmosphere. The first step of the processing, Level 1b, consists of various instrumental corrections to obtain the measured atmospheric spectral transmission as a function of altitude/geolocation. The second step (Level 2) consists of one spectral inversion for each line of sight (retrieval of integrated line densities of various constituents) and one vertical inversion for the whole occultation. The analysis of two fast photometers (1kHz) data will produce a high resolution profile for the temperature profile. Higher data products will be constructed with the sequential assimilation of GOMOS data into a CTM model.
The paper proposes a reliable method for estimating quadric surfaces from 3d range data in the framework of object recognition and localization or object modelling. Instead of estimating a quadric surface individually...
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The paper proposes a reliable method for estimating quadric surfaces from 3d range data in the framework of object recognition and localization or object modelling. Instead of estimating a quadric surface individually, the approach fits all the surfaces captured in the scene together, taking into account the geometric relationships between them and their specific characteristics. The technique is compared with other methods through experiments performed on real objects.
The work is concerned with the signal-to-symbol problem of building skinned, segmented, landmarked and labeled3d models of the whole human body from range data. A fully automated model based process is presented that...
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The work is concerned with the signal-to-symbol problem of building skinned, segmented, landmarked and labeled3d models of the whole human body from range data. A fully automated model based process is presented that takes raw range data, cleans and skins it, and then locates "interesting" features, to enrich the surface with symbolic information for specific applications. The method is validated via volumetrics in medicine and surface anthropometry.
An interacting fusion and vergence system is presented which utilizes two properties of coherence-based stereo: sub-pixel-precision and a stable validation signal for disparity estimates. This allows the system to sam...
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An interacting fusion and vergence system is presented which utilizes two properties of coherence-based stereo: sub-pixel-precision and a stable validation signal for disparity estimates. This allows the system to sample the three-dimensional scene with several precisely chosen fixation points and automatically accumulate the data into a full disparity map. In addition, the system creates a fused cyclopean view of the scene, co-registered with the final disparity map.
The problem of estimating and tracking the pose of a 3d object is a well-established problem in machine vision with important applications in terrestrial and space robotics. The paper describes how 3d range data, avai...
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The problem of estimating and tracking the pose of a 3d object is a well-established problem in machine vision with important applications in terrestrial and space robotics. The paper describes how 3d range data, available from a new generation of real time laser rangefinding systems, can be used to solve the pose determination problem. The approach is based on analysis of the local geometric structure encoded in the range data to extract landmarks. Local configurations of these landmarks provide estimates of identity and pose through matching against a nominal model using a Bayesian optimization technique. Aggregates of local estimates are used to provide a robust estimate of global pose. The technique is well suited to space tracking applications for which examples are provided.
The CAESAR study (Civilian American and European Surface Anthropometry Resource) is a survey of body measurements for people ages 18-65 in three countries: USA, The Netherlands, and Italy. It is a collaborative effort...
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The CAESAR study (Civilian American and European Surface Anthropometry Resource) is a survey of body measurements for people ages 18-65 in three countries: USA, The Netherlands, and Italy. It is a collaborative effort with partners from several countries and many industries. It employs the latest in 3d measurement technology, and is the first 3d surface anthropometry survey of the US and Europe. data from the study will allow us to effectively design everything from better fitting clothes and protective equipment to better seats and workstations, as well as dramatically reducing the cost to design and manufacture them.
We present a novel geometric approach to extract planes from sets of 3d points. For a set with n points the algorithm has an O(n/sup 3/ log n) time complexity. We also discuss an implementation of the algorithm for ra...
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We present a novel geometric approach to extract planes from sets of 3d points. For a set with n points the algorithm has an O(n/sup 3/ log n) time complexity. We also discuss an implementation of the algorithm for range image segmentation. The performance of the new range image segmentation algorithm is compared to other existing methods.
The calibration of a laser stripe profiler consisting of a laser stripe projector camera and a linear motion table is considered. A nonlinear system model is used which accommodates radial distortion in the camera len...
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The calibration of a laser stripe profiler consisting of a laser stripe projector camera and a linear motion table is considered. A nonlinear system model is used which accommodates radial distortion in the camera lens. The way in which stripe data is extracted from the camera images lends to a natural formulation of the calibration problem as a nonlinear least squares problem. This can then be solved using standard techniques.
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